Probability and statistics

This book is the first to focus on the global flow of funds (GFF), providing an introduction to its fundamental concepts and establishing a theoretical framework for analysis.

When data is collected on failure or survival a list of times is obtained.

All students and professionals in statistics should refer to this volume as it is a handy reference source for statistical formulas and information on basic probability distributions.

This book systematically presents the topological structure of solution sets and attractability for nonlinear evolution inclusions, together with its relevant applications in control problems and partial differential equations.

This book is an introduction to financial mathematics.

A unique introduction to the innovative methodology of statistical flowgraphs This book offers a practical, application-based approach to flowgraph models for time-to-event data.

This volume consists of three parts: Part I comprises 11 chapters on the basic concepts of statistics, Part II consists of 10 chapters on multivariate statistics and Part III contains 12 chapters on design and analysis for medical research.

Shapes have been among man's fascinations from thestoneage to thespace age.

The sequential quadratic hamiltonian (SQH) method is a novel numerical optimization procedure for solving optimal control problems governed by differential models.

In this book, the subject of design and analysis of experiments has been covered in simple language by giving basic concepts of various designs and essential data analysis steps of designed experiments.

This book is a convenient and comprehensive guide to statistics.

In many areas of science a basic task is to assess the influence of several factors on a quantity of interest.

What happens when the sport of Juggling meets a Statistical Process Control class?

This research monograph presents results to researchers in stochastic calculus, forward and backward stochastic differential equations, connections between diffusion processes and second order partial differential equations (PDEs), and financial mathematics.

Learning and Generalization provides a formal mathematical theory addressing intuitive questions of the type: How does a machine learn a concept on the basis of examples?

This book constitutes the refereed proceedings of the 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, held as a virtual event, in June 2021.

Morphometrical differentiation 63 Prediction of breeding origin .

An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes necessary in understanding and applying stochastic methods to biological problems in areas such as population growth and extinction, drug kinetics, two-species competition and predation, the spread of epidemics, and

Useful in physics, economics, psychology, and other fields, random matrices play an important role in the study of multivariate statistical methods.

The definitive textbook on stochastic processes, written by one of the world''s leading information theorists, covering both theory and applications.

This book explains how to determine sample size for studies with correlated outcomes, which are widely implemented in medical, epidemiological, and behavioral studies.

In recent years, as part of the increasing "e;informationization"e; of industry and the economy, enterprises have been accumulating vast amounts of detailed data such as high-frequency transaction data in nancial markets and point-of-sale information onindividualitems in theretail sector.

This book explores the independence of official statistics and describes the various legal and professional norms, institutional arrangements, instruments and practices that statisticians have developed over recent decades to protect their work from political interference.

This handbook is a comprehensive reference guide for researchers, funding agencies and organizations engaged in survey research.

Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models.

This book is not a research monograph about Malliavin calculus with the latest results and the most sophisticated proofs.

This volume presents theoretical developments, applications and computational methods for the analysis and modeling in behavioral and social sciences where data are usually complex to explore and investigate.

This text introduces and provides instruction on the design and analysis of experiments for a broad audience.

This book presents essential tools for modelling non-linear time series.

The study of the ocean is almost as old as the history of mankind itself.

An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling.

Statistics is the activity of inferring results about a population given a sample.

This book presents the refereed proceedings of the Seventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, held in Ulm, Germany, in August 2006.

This book constitutes the joint refereed proceedings of the 17th International Conference on Next Generation Wired/Wireless Advanced Networks and Systems, NEW2AN 2017, the 10th Conference on Internet of Things and Smart Spaces, ruSMART 2017.

The Volume 1 book on Accelerating Discoveries in Data Science and Artificial Intelligence (Proceedings of ICDSAI 2023), that was held on April 24-25, 2023 by CSUSB USA, the International Association of Academicians (IAASSE), and the Lendi Institute of Engineering and Technology, Vizianagaram, India is intended to be used as a reference book for researchers and practitioners in the disciplines of AI and data science.

This book employs a computable general equilibrium (CGE) model - a widely used economic model which uses actual data to provide economic analysis and policy assessment - and applies it to economic data on Singapore's tourism industry.

This is a unique volume by a unique scientist, which combines conceptual, formal, and engineering approaches in a way that is rarely seen.

This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics.

Bayesian Networks: With Examples in R, Second Edition introduces Bayesian networks using a hands-on approach.

This book focuses on the structural analysis of demand under block rate pricing, a type of nonlinear pricing used mainly in public utility services.

A concise, elementary introduction to measure and integration theory, requiring few prerequisites as theory is developed quickly and simply.

First Published in 2017.

This book provides a comprehensive and unified introduction to stochastic differential equations and related optimal control problems.

The integrated nested Laplace approximation (INLA) is a recent computational method that can fit Bayesian models in a fraction of the time required by typical Markov chain Monte Carlo (MCMC) methods.

The book presents, for the first time, a detailed analysis of harmonizable processes and fields (in the weak sense) that contain the corresponding stationary theory as a subclass.